Biologically-inspired self-supervised systems

Project leader: Dario Zanca
Project members: Leo Schwinn, Björn Eskofier
Start date: 1. January 2022
End date:
Funding source: Internally funded

Abstract

The aim of this project is to develop self-supervised learning systems under biological constraints. This has the twofold advantage of providing biologically plausible computational models, as well as delivering more interpretable decision makers, capable of operating under resource-constrained conditions.